Tag: data mining

6 key ways advertisers can benefit from predictive analytics and how to get started Predictive Analytics, in its simplest definition, is just the process of using historical data to detect patterns and build predictions for future outcomes based on similar patterns repeating in the future. In advertising, this might include examples like using historical performance data from digital advertising campaigns on Google to build predictions of how similar campaigns might perform in the future. Unlike other forms of analytics - like dashboarding and Business Intelligence (BI) - also known as “descriptive analytics,” predictive analytics relies on mathematical algorithms to predict future outcomes. It’s a powerful tool for optimizing advertising spend. Why Predictive Analytics in Advertising? Predictive analytics, driven by Machine Learning, can be a powerful tool for data-heavy industries. The world of advertising, especially digital advertising, relies heavily on data but has recently been subjected to seismic shifts due to…

What is Data Mining? Data mining is the process of analyzing data to uncover hidden knowledge; this is also known as knowledge discovery. The data is analyzed to find patterns and other valuable information that can benefit our business. Data mining is performed by analyzing large amounts of usually raw data and applying different techniques to extract patterns and information that can help businesses make decisions, mitigate risks, optimize their processes, better allocate their funds, and many more. Regression Analysis Regression analysis is one of the methods we use in predictive data mining. With the help of statistics, it established the relationship between several variables. The two main types are logistic and simple/multiple linear regression. Logistic regression is used when we try to predict whether an example will fall into one of the two classes. Logistic regression examples: Spam Detection: Predicting if the email is spam, Medicine: Predicting if a…